Visibility Detection Method Based on Automatic Image Recognition

Abstract

Visibility detection has great research and practical application value in the fields of weather forecasting and autonomous driving. At the same time, the existing visibility detection methods have some problems, such as the high price of hardware equipment, the need to set specific markers, and the large amount of calculation. In this paper, a visibility detection algorithm based on automatic image recognition is proposed, which calculates the light intensity of the target area of the image through a series of image processing, calculates the corresponding transmittance through the dark channel prior algorithm, and then inverts the atmospheric visibility according to the Koschmieder atmospheric visibility measurement principle. The corresponding fog concentration coefficient under different visibility conditions was measured by experiments, and the visibility value calculated based on the image and the visibility value of the CJY-1G forward visibility scattering instrument were compared, and the error percentage before the two was calculated, so as to verify that the visibility value detected by the method used in this chapter can fully meet the specified error range and meet the application requirements of visibility observation.